Data Engineer

As a Data Engineer, you will transform complex datasets into meaningful insights to drive data-driven decisions across HR, Finance, and Operations. You’ll work closely with AI Engineers, Data Scientist, and stakeholders to develop models, dashboards, and predictive analytics systems. Core Responsibilities:

Design and maintain scalable ETL pipelines to process structured and unstructured data from multiple sources.

Build and optimize data warehouses, data lakes, and data marts to support downstream analytics and AI systems.

Collaborate closely with data scientists and AI engineers to ensure clean, accessible, and reliable data.

Implement data quality checks, monitoring, and logging to ensure data integrity and lineage.

Automate data workflows using tools like Airflow, dbt, or custom Python scripts.

Work with both structured (MySQL, PostgreSQL) and non-structured (pdf, images, ppt and many more) data sources.

Ensure secure, efficient, and governed access to enterprise-grade datasets and APIs.

Continuously improve data infrastructure based on usage feedback, scalability needs, and business goals.

Must-Have Skills

Proficient in SQL and one programming language (Python, Scala, or Java)

Solid understanding of data modeling, ETL design, and batch/streaming data processing

Hands-on experience with modern data pipeline tools (e.g., Apache Airflow, dbt, or similar)

Familiar with both relational (PostgreSQL, MySQL) and non-relational (MongoDB, S3, etc.) databases

Experience working with large datasets and optimizing performance for data queries and storage

Comfortable collaborating with data scientists, analysts, and backend engineers